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P. Bodesinsky, B. Alsallakh, T. Gschwandtner, S. Miksch:
"Visual Process Mining: Event Data Exploration and Analysis";
Poster: Ieee Vis 2014, Paris, France; 09.11.2014 - 14.11.2014; in: "VAST Poster Proceedings of the IEEE Visualization Conference (VIS 2014)", G. Andrienko, E. Bertini, H. Carr, N. Elmqvist, B. Lee, H. Leitte (Hrg.); (2014), 2 S.

The research field of Process Mining deals with the extraction of information from event logs. Since large amounts of event data are generated every day, analyzing these often unstructured event logs poses a research challenge. To cope with the complexity of the data and the associated mining tasks, appropriate visualizations and interactive means are needed. We present our early prototype for the visual exploration of event sequences and patterns. Our approach combines (1) a visual representation of event sequences emphasizing recurring event patterns, (2) automated pattern mining methods, as well as (3) interactive means for exploration. We provide first steps to support browsing event logs in an interactive environment and to facilitate the inspection of recurring pattern locations within the context of the surrounding events.

visual process mining, arc diagrams, pattern detection, event log data

http://publik.tuwien.ac.at/files/PubDat_234178.pdf

Projektleitung Silvia Miksch:
CVAST: Centre for Visual Analytics Science and Technology (Laura Bassi Centre of Expertise)